Autonomous Systems & HRI AI Research Fellow

Johns Hopkins University; Baltimore (MD); On-site; USD 70,000 - 100,000; Full time

Job summary

Johns Hopkins University seeks a PREP Research Associate to support the NIST PREP program in Gaithersburg, MD. The role focuses on evaluating AI capabilities in autonomous and human-robot interaction systems, advancing testing methods, metrics and verification frameworks.

Responsibilities include conducting state-of-the-art robotics and AI research, applying deep learning, LLMs, reinforcement learning, and probabilistic methods, developing benchmarks, digital twins, and testbeds, and

Qualifications

• Ph.D. or equivalent experience in natural sciences, engineering, or related fields.
• Innovative thinking and strong experimental skills.
• Ability to work both independently and collaboratively.
• Effective written and oral communication skills.
• Prior hands-on experience in micro-/nanofabrication; integrated photonics design and characterization; PIC design; numerical simulations; device-level metrology.

Responsibilities

• Conduct state-of-the-art measurement science research in robotics, advanced autonomy, and AI systems.
• Apply deep learning, LLMs, reinforcement learning, and unsupervised ML to enhance robot capabilities and decision-making.
• Develop verification methods, transparent evaluation frameworks, and performance metrics for inspectable robotic AI systems.
• Implement advanced filtering and symbolic spatial relation models to optimize tracking, navigation, and behavior classification.

Skills

Deep learning

Experimentation

Independent work

Communication

Education

Ph.D. or equivalent

Tools

3D rendering

CAD

Sensor fusion tools

Job description

Johns Hopkins University seeks a PREP Research Associate to support the NIST PREP program in Gaithersburg, MD. The role focuses on evaluating AI capabilities in autonomous and human-robot interaction systems, advancing testing methods, metrics and verification frameworks.

Responsibilities include conducting state-of-the-art robotics and AI research, applying deep learning, LLMs, reinforcement learning, and probabilistic methods, developing benchmarks, digital twins, and testbeds, and